Building Defect Prediction Models in Practice
IEEE Software
Determining noisy instances relative to attributes of interest
Intelligent Data Analysis
The pairwise attribute noise detection algorithm
Knowledge and Information Systems - Special Issue on Mining Low-Quality Data
Detecting noisy instances with the rule-based classification model
Intelligent Data Analysis
Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm
Intelligent Data Analysis
A comprehensive empirical evaluation of missing value imputation in noisy software measurement data
Journal of Systems and Software
The multiple imputation quantitative noise corrector
Intelligent Data Analysis
Software quality analysis by combining multiple projects and learners
Software Quality Control
Knowledge discovery from imbalanced and noisy data
Data & Knowledge Engineering
Empirical case studies in attribute noise detection
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
Dealing with noise in defect prediction
Proceedings of the 33rd International Conference on Software Engineering
An industrial case study of classifier ensembles for locating software defects
Software Quality Control
A novel classification algorithm to noise data
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
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Predicting when and how a software system will evolve is one of the most fascinating challenges of software engineering. No matter what approach one is using to study such evolution, empirical studies, including observations of systems used in the real ...